Guangyao Chen

CGY4.jpeg

I’m currently a Postdoctoral Associate at AI for Science Institute, Cornell University. I received my Ph.D. degree at School of Computer Science, Peking University. I received my Bachelor degree in Computer Science from Wuhan University in 2018.

My research vision is to devise an efficient, reliable, and autonomous AI system that can operate in the open world. Guided by the principles of efficiency, reliability, and autonomy, I concentrate on these crucial aspects to enhance and adapt AI models:

  • Autonomous Agent: constructing efficient and robust autonomous LLM-based agent systems that leverage LLMs to accomplish automated planning, reasoning, learning, and collaboration.
  • Open World Learning: boosting the robustness of efficient AI models in the open world, achieving adaptation to diverse distributions, and discovering and learning new categories.
  • AI for Science: using AI technology to determine the best manufacturing conditions for nanoparticle materials and accelerate the discovery of materials.

Feel free to catch me if interested to discuss ideas or work together. 😜

news

2025.05  🎉🎉 Three papers (two spotlight papers) are accepted by the conference ICML 2025.
2025.04  🎉🎉 One paper on LLMs for Material is accepted by the journal Advanced Materials.
2025.03  🎉🎉 One workshop paper (spotlight presentation) is accepted by the conference CVPR 2025.
2024.11  🎉🎉 I awared the CSIG 2024 Outstanding PhD Thesis Award (10 people nationwide).
2024.09  🎉🎉 One paper on Visual RL are accepted by the conference NeurIPS 2024.
2024.07  🎉🎉 Two papers on Few-shot Learning are accepted by the conference ACMMM 2024.
2024.04  🎉🎉 One paper on Autonomous Agent is accepted by the conference IJCAI 2024.
2023.12  🎉🎉 One paper on Incremental Novel Class Discovery is accepted by the conference AAAI 2024.
2023.11 Invited talk at Qingyuan Workshop (Online).
2023.11 Invited talk at RLChina 2023 in Suzhou.
2023.06 I receive my Ph.D. degree in computer science from Peking University with Outstanding Doctoral Dissertation Award.
2022.09  🎉🎉 Two papers on Image-based Reinforcement Learning and Out-of-Distribution Detection are accepted by the conference NeurIPS 2022.

selected publications

  1. ICML
    When Every Millisecond Counts: Real-Time Anomaly Detection via the Multimodal Asynchronous Hybrid Network
    Dong Xiao*, Guangyao Chen*†, Peixi Peng, Yangru Huang, Yifan Zhao, and 2 more authors
    In Forty-second International Conference on Machine Learning, 2025 (Spotlight Poster, Acceptance Rate: < 2.6%)
    Paper
  2. IJCAI
    AutoAgents: A Framework for Automatic Agent Generation
    Guangyao Chen*, Siwei Dong*, Yu Shu*, Ge Zhang, Sesay Jaward, and 3 more authors
    In The 33rd International Joint Conference on Artificial Intelligence, 2024 (Acceptance Rate: 15%)
    arXiv Code
  3. AAAI
    Adaptive Discovering and Merging for Incremental Novel Class Discovery
    Guangyao Chen, Peixi Peng, Yangru Huang, Mengyue Geng, and Yonghong Tian
    In Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
    arXiv Paper
  4. ACMMM
    MICM: Rethinking Unsupervised Pretraining for Enhanced Few-shot Learning
    Zhenyu Zhang*, Guangyao Chen*, Yixiong Zou, Zhimeng Huang, Yuhua Li, and 1 more author
    In ACM Multimedia, 2024 (Oral Presentation, Acceptance Rate: < 3.97%)
    Paper
  5. ACMMM
    Learning Unknowns from Unknowns: Diversified Negative Prototypes Generator for Few-shot Open-Set Recognition
    Zhenyu Zhang*, Guangyao Chen*, Yixiong Zou, Yuhua Li, and Ruixuan Li
    In ACM Multimedia, 2024
    Paper
  6. TPAMI
    Adversarial Reciprocal Points Learning for Open Set Recognition
    Guangyao Chen, Peixi Peng, Xiangqian Wang, and Yonghong Tian
    IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 (Academician Shi Qingyun’s Outstanding Paper Award, Highly Cited Paper)
    arXiv Paper Code
  7. ICCV
    Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain
    Guangyao Chen, Peixi Peng, Li Ma, Jia Li, Lin Du, and 1 more author
    In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), Oct 2021
    arXiv Paper Code
  8. ECCV
    Learning open set network with discriminative reciprocal points
    Guangyao Chen, Limeng Qiao, Yemin Shi, Peixi Peng, Jia Li, and 3 more authors
    In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part III 16, Oct 2020 (Spotlight Presentation, Acceptance Rate: < 5%)
    arXiv Paper Dataset Code